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Evidence row 541007

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint e02856ce-442f-456c-a7b2-62fc1f55ed3c
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
f46a33b155ef38a8162c09ed1b18779acec756108cebda10027e0cb8c30f944f
Leaf
0xc854a1a40223ee87359f8c49780948b8bc4e9c16d2fb62e6769a1d8eaa090d55

What was observed

{
  "count": 5,
  "tools": [
    {
      "description": "Static-analyze a public GitHub repo (owner/name) or a set of source files for LLM token waste: uncached static prompts, frontier models on extraction tasks, hot loops, non-deterministic repeat calls. Returns findings with fixes and an estimated recoverable percentage.",
      "inputSchema": {
        "properties": {
          "files": {
            "description": "Alternative to repo: files to analyze",
            "items": {
              "properties": {
                "content": {
                  "type": "string"
                },
                "path": {
                  "type": "string"
                }
              },
              "required": [
                "path",
                "content"
              ],
              "type": "object"
            },
            "type": "array"
          },
          "repo": {
            "description": "GitHub owner/name (public)",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "audit_repo_token_waste"
    },
    {
      "description": "Price a workload at list prices across models: cost per request and per month for the requested model, its cheaper sibling, and the effect of prompt caching. Pricing table version 2026-10-26.",
      "inputSchema": {
        "properties": {
          "compare_to": {
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "input_tokens": {
            "type": "number"
          },
          "model": {
            "type": "string"
          },
          "output_tokens": {
            "type": "number"
          },
          "requests_per_month": {
            "type": "number"
          },
          "static_tokens": {
            "description": "portion of input_tokens that is a fixed prefix (system + tools)",
            "type": "number"
          }
        },
        "required": [
          "model",
          "input_tokens",
          "output_tokens"
        ],
        "type": "object"
      },
      "name": "calculate_model_arbitrage"
    },
    {
      "description": "Rewrite an OpenAI Chat/Responses or Anthropic Messages request body so its static prefix is provider-cacheable (Anthropic cache_control breakpoints, OpenAI prompt_cache_key). Returns the optimized body, what changed, the token profile and the projected per-request saving. Never changes the tokens the model sees.",
      "inputSchema": {
        "properties": {
          "body": {
            "description": "The request body",
            "type": "object"
          },
          "endpoint": {
            "enum": [
              "/v1/chat/completions",
              "/v1/responses",
              "/v1/messages"
            ],
            "type": "string"
          },
          "strategy": {
            "enum": [
              "static",
              "conversation"
            ],
            "type": "string"
          }
        },
        "required": [
          "body"
        ],
        "type": "object"
      },
      "name": "optimize_prompt_payload"
    },
    {
      "description": "Create a TokenZero workspace and key with no form. Returns the key once, the base URLs that route through it (OPENAI_BASE_URL / ANTHROPIC_BASE_URL), the one-click dashboard link and the badge URL. Free up to the monthly free tier; nothing is billed.",
      "inputSchema": {
        "properties": {
          "name": {
            "description": "workspace name (default mcp-agent)",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "provision_workspace"
    },
    {
      "description": "Live value scorecard for a TokenZero workspace: hard savings and net ROI per window, the four engines' contribution, speed, parity, availability and privacy posture, per-model breakdown and one-click recommendations. Needs the workspace key (tz_live_…); pass demo: true for a labelled sample.",
      "inputSchema": {
        "properties": {
          "demo": {
            "description": "return the sample scorecard instead",
            "type": "boolean"
          },
          "key": {
            "description": "workspace key (tz_live_…)",
            "type": "string"
          },
          "window": {
            "enum": [
              "24h",
              "7d",
              "30d",
              "all"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "workspace_metrics"
    }
  ]
}

What the leaf hashes

{"body":"f46a33b155ef38a8162c09ed1b18779acec756108cebda10027e0cb8c30f944f","id":541007,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793130191820000,"prev":null,"subject":"e02856ce-442f-456c-a7b2-62fc1f55ed3c","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (273461 rows).

  1. 0xc85462d12117ea716fa157173102a2cfd3dfbd0546fbb09321367f2dc1479880
  2. 0x14af563ad35fe16ed2005dc077c9e09b156ae5b480b5692acefce5919227a0e3
  3. 0xc3cb6e6a10d85080fb584fd752f8aec3833b4404691bb7e1c140e665d4b8cb19
  4. 0x703524565502cc8c39b6305e125d749dfa45cf4b07ebc2104e0566e88227852e
  5. 0x0e386ac97a02f74afc60400f769354111be3cae8b8ffedbcba7b3d68f8e26a37
  6. 0x6cd84fd0f17592122ca3288d7e73cb3a2db7c7d0e6ed93ba5b6ff8e864308385
  7. 0x7a8191053c134cd41d17ecc53b5625cade47d6cfd3364844c7db58697c698e28
  8. 0x56b7599d5e9d2d6967a18dc5d195a68c1213a111e3f3ec0fba4d809439dfb24d
  9. 0xf4de46e2b707dea4c98d7102d6c63c517e48b4b0f5b23cc78b71e54eacf87cb8
  10. 0xbfaf40e8c4f3a485ca887e2403dd98c5474d6af3e3f929d0f705767f8e82a946
  11. 0x057a79dae7284d2b0542272663bf1bcad5f3c4a13e38a7fdd7392ad650b50c86
  12. 0xd16d7e5f125e1d777c4add2d34626605aa2a6b03288469395f9c1f401de8e9e1
  13. 0x938752e9acd199cd15f468392bc2dd8eefc52293e7144e30b87b241ca6b2513b
  14. 0xcc49fd573532e5a29f5be4033f62a2eff71456c020bd2258312b98e95cfe301e
  15. 0x969cd44e5a4e8dc3110540398fbf689659eb51df735c1cda5d8f021ef9ff5683
  16. 0xa94627de1af0e823832e05a9069b304ecccb8c0cdb8f9cfc4f2039bfb9799dc5
  17. 0xdf1105afdc109de3c09a98fc8a3864159ad964e6f49b635c105a27a1e1f14310
  18. 0x2bf8151e5f157dd183b9de6fa00469551932a7a6e3f33a694895000ac9061197
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON